Exploring equipment electrocardiogram mechanism for performance degradation monitoring in smart manufacturing
journal contributionposted on 2021-03-29, 07:51 authored by Baotong Chen, Jiafu Wan, Min Xia, Eve ZhangEve Zhang
Similar to the use of electrocardiogram (ECG) for monitoring heartbeat, this article proposes an equipment electrocardiogram (EECG) mechanism based on fine-grained collection of data during the entire operating duration of the manufacturing equipment, with the purpose of the EECG to reveal the equipment performance degradation in smart manufacturing. First, the system architecture of EECG in smart manufacturing is constructed, and the EECG mechanism is explored, including the granular division of the duration of the production process, the matching strategy for process sequences, and several important working characteristics (e.g., baseline, tolerance, and hotspot). Next, the automatic production line EECG (APL-EECG) is deployed, to optimize the cycle time of the production process and to monitor the performance decay of the equipment online. Finally, the performance of the APL-EECG was validated using a laboratory production line. The experimental results have shown that the APL-EECG can monitor the performance degradation of the equipment in real-time and can improve the production efficiency of the production line. Compared with a previous factory information system, the APL-EECG has shown more accurate and more comprehensive understanding in terms of data for the production process. The EECG mechanism contributes to both equipment fault tracking and optimization of production process. In the long run, APL-EECG can identify potential failures and provide assistance in for preventive maintenance of the equipment.
Joint Fund of the National Natural Science Foundation of China and Guangdong Province under Grant U1801264
Guangdong Province Key Areas R&D Program under Grant 2019B010150002 and Grant 2019B090919002
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering